Method for detecting surface defects of mechanical parts based on image texture and fractal dimension

A technology of fractal dimension and mechanical parts, applied in image analysis, image data processing, measuring devices, etc., can solve problems that do not conform to the actual observation of the human eye, and achieve simple and easy actual observation of the human eye and meet the actual observation of the human eye Effect

Inactive Publication Date: 2010-05-19
HANGZHOU DIANZI UNIV
View PDF0 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, traditional machine vision quality evaluation methods based on peak-to-noise ra

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for detecting surface defects of mechanical parts based on image texture and fractal dimension
  • Method for detecting surface defects of mechanical parts based on image texture and fractal dimension
  • Method for detecting surface defects of mechanical parts based on image texture and fractal dimension

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0027] A method for detecting surface defects of mechanical parts based on image texture and fractal dimension includes the following steps:

[0028] Step (1). Pre-processing the mechanical parts to be tested. The specific method of pre-processing is to first coat the surface of the part to be tested with black ink, and then wipe the surface of the part with a dry cloth after the ink fills the pores of the part to be tested;

[0029] Step (2), place the pre-processed mechanical parts on the conveyor belt, and use the CCD image acquisition system to image the surface of the part to be measured to obtain the texture image of the surface of the part;

[0030] Step (3): Calculate the fractal dimension and voidness of the texture image;

[0031] The method of calculating the fractal dimension of the texture image is:

[0032] The surface image of the mechanical part is expanded by several zero rows or several zero columns at the corresponding boundary to make the width and height of the imag...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a method for detecting surface defects of mechanical parts based on image texture and fractal dimension. Traditional methods for detecting surface defects of mechanical parts have the disadvantages of low efficiency and low detecting accuracy. The method comprises the following steps of: firstly preprocessing mechanical parts to be detected, placing the preprocessed mechanical parts on a conveyor belt, acquiring an image of a part surface to be detected with a CCD image acquisition system to obtain a texture image of the part surface; then calculating the fractal dimension and the voidage of the texture image; and finally matching and comparing the calculated fractal dimension and the calculated voidage of the texture image with those of a standard part in a mechanical part database. The invention can realize the evaluation of the machine visual quality by calculating the fractal dimension and the voidage features representing subjective perceptions based on the external features of the surface defect texture of mechanical parts.

Description

technical field [0001] The invention belongs to the technical field of machine vision, and in particular relates to a method for detecting surface defects of mechanical parts based on image texture and fractal dimension. Background technique [0002] At present, mechanical parts are widely used in the automobile industry, aviation industry, medical industry, etc., and the automatic and precise detection of surface defects of mechanical parts is a very important link in the production process. The accuracy of the detection system directly affects the classification of products and the quality of products. One of the key technologies for improving the detection system to identify surface defects of mechanical parts is to select an appropriate quality evaluation method. At present, the detection systems used in the production process of mechanical parts in my country mostly use subjective evaluation. Therefore, the evaluation process is inefficient, and the evaluation results ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01N21/898G06T7/00
Inventor 范影乐沈学丽詹跃荣陈可耿丽硕何攀
Owner HANGZHOU DIANZI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap